Abstract
Face recognition performance in operational scenarios is can be improved by using cameras that capture multispectral or hyperspectral images at specific bands within the visible spectrum. Band-selected images have shown promise to improve face recognition performance, but the requisite camera systems needed to achieve multi-filter or hyperspectral imaging are often to complex and cost-prohibitive for many law enforcement applications. In order to find a more cost-effective solution, the work presented here aims to determine if simple band-filtered images, captured by placing bandpass filters on conventional RGB imagers, show any application advantages over broad-spectrum visible facial imagery. After data collection was completed, matching studies were performed to determine what performance enhancement, if any, is gained using band-filtered imaging. Results indicate that image quality may play a bigger role in the facial recognition performance of band-filtered images rather than simple band-filtering alone, warranting further study in this area.
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Dawson, J., Goodwyn, J., Means, S., Crakes, J. (2020). Quality and Match Performance Analysis of Band-Filtered Visible RGB Images. In: Bourlai, T., Karampelas, P., Patel, V.M. (eds) Securing Social Identity in Mobile Platforms. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-39489-9_6
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